TY - JOUR
T1 - Detection of Water Leakage in Underground Tunnels Using Corrected Intensity Data and 3D Point Cloud of Terrestrial Laser Scanning
AU - Xu, Teng
AU - Xu, Lijun
AU - Li, Xiaolu
AU - Yao, Junen
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/5/31
Y1 - 2018/5/31
N2 - Detection of water leakage is one of the most important regular tasks for underground tunnel inspection. In this paper, a new method is proposed for the water leakage detection in underground tunnels by using the corrected intensity data and 3-D point cloud of a terrestrial laser scanning (TLS) sensor. In the proposed method, the distance effect on the TLS intensity is first corrected based on a piecewise linear interpolation by using a reference target. Then, the distance-corrected intensity data are used to determine the surface roughness parameter that is specially considered to correct the incident angle effect. After corrections of distance and incident angle effects, the corrected intensity data are used to detect the water leakage regions in the underground tunnel. Finally, the appendages on the tunnel wall are removed by using the 3-D point cloud data to eliminate their influence on water leakage detection. To validate the feasibility of the proposed method, a case study in an underground tunnel in Beijing, China, was conducted by using a TLS sensor. Experimental results have demonstrated that the water leakage regions in the underground tunnel can be well extracted by using the corrected intensity data and 3-D point cloud, especially when the surface roughness is considered.
AB - Detection of water leakage is one of the most important regular tasks for underground tunnel inspection. In this paper, a new method is proposed for the water leakage detection in underground tunnels by using the corrected intensity data and 3-D point cloud of a terrestrial laser scanning (TLS) sensor. In the proposed method, the distance effect on the TLS intensity is first corrected based on a piecewise linear interpolation by using a reference target. Then, the distance-corrected intensity data are used to determine the surface roughness parameter that is specially considered to correct the incident angle effect. After corrections of distance and incident angle effects, the corrected intensity data are used to detect the water leakage regions in the underground tunnel. Finally, the appendages on the tunnel wall are removed by using the 3-D point cloud data to eliminate their influence on water leakage detection. To validate the feasibility of the proposed method, a case study in an underground tunnel in Beijing, China, was conducted by using a TLS sensor. Experimental results have demonstrated that the water leakage regions in the underground tunnel can be well extracted by using the corrected intensity data and 3-D point cloud, especially when the surface roughness is considered.
KW - Intensity correction
KW - surface roughness
KW - terrestrial laser scanning
KW - underground tunnel
KW - water leakage
UR - https://www.scopus.com/pages/publications/85047988510
U2 - 10.1109/ACCESS.2018.2842797
DO - 10.1109/ACCESS.2018.2842797
M3 - 文章
AN - SCOPUS:85047988510
SN - 2169-3536
VL - 6
SP - 32471
EP - 32480
JO - IEEE Access
JF - IEEE Access
ER -